key: cord-0891798-m5m3mel8
authors: Wong, Eric Kai Chung; Watt, Jennifer; Zou, Hanyan; Chandraraj, Arthana; Zhang, Alissa W.; Norman, Richard; Piggott, Katrina Lynn; Straus, Sharon E.; Liu, Barbara
title: Mortality in hospitalized older adults with COVID‐19 during three waves: A multicenter retrospective cohort study
date: 2022-04-13
journal: Health Sci Rep
DOI: 10.1002/hsr2.603
sha: ee154d7854ce0b38be8512c68fc8ac4b43439628
doc_id: 891798
cord_uid: m5m3mel8

BACKGROUND: The waves of COVID‐19 infections in Ontario, Canada, were marked by differences in patient characteristics and treatment. Our objectives were to (i) describe patient characteristics, treatment, and outcomes of hospitalized older adults with COVID‐19 between waves 1, 2, and 3, (ii) determine if there was an improvement in in‐hospital mortality in waves 2 and 3 after adjusting for covariates. METHODS: This retrospective cohort study was done in five acute care hospitals in Toronto, Ontario. Consecutive hospitalized older adults aged ≥65 years with confirmed COVID‐19 infection were included. Wave 1 extended from March 11 to July 31, 2020, wave 2 from August 1, 2020 to February 20, 2021, and wave 3 from February 21 to June 30, 2021. Patient characteristics and outcomes were abstracted from charts. A logistic regression model was used to determine the association between COVID‐19 and in‐hospital mortality in waves 2 and 3 compared with wave 1. RESULTS: Of the 1671 patients admitted to acute care, 297 (17.8%) were admitted in wave 1, 751 (44.9%) in wave 2, and 623 (37.3%) in wave 3. The median age of our cohort was 77.0 years (interquartile range: 71.0–85.0) and 775 (46.4%) were female. The prevalence of frailty declined in progressive waves. The use of dexamethasone, remdesivir, and tocilizumab was significantly higher in waves 2 and 3 compared with wave 1. In the unadjusted analysis, in‐hospital mortality was unchanged between waves 1 and 2, but it was lower in wave 3 (18.3% vs. 27.4% in wave 1). After adjustment, in‐hospital mortality was unchanged in waves 2 and 3 compared with wave 1. CONCLUSION: In‐hospital mortality in hospitalized older adults with COVID‐19 was similar between waves 1 and 3. Further research should be done to determine if COVID‐19 therapies have similar benefits for older adults compared with younger adults.

The COVID-19 pandemic was marked by multiple waves as the infection waxed and waned. In Ontario, Canada, the waves of COVID-19 infection were related to seasonality, 1 changes in public health measures, 2 and the emergence of new COVID-19 strains. 3 Little was known about the treatment of COVID-19 during the first wave, which predominantly affected older adults. 4 When the second wave started on August 1, 2020, 5 there was more familiarity with isolation measures and more treatments available ( Figure S1 ). 6 Several therapies were demonstrated to be effective for hospitalized COVID-19 patients in waves 2 and 3, including dexamethasone, 8 remdesivir, 9 and tocilizumab, 10 but data on older adults were limited. Vaccinations in long-term care (LTC) homes reduced hospitalizations in wave 2, but community-dwelling older adults were not vaccinated until late in the second wave. 11 Despite vaccinations, some older adults continue to be at risk for severe disease and hospitalization. 12 Given the improvement in pharmacologic and nonpharmacologic treatment of COVID-19, we wanted to determine if mortality was improved in hospitalized older adults with COVID-19 in waves 2 and 3 compared to wave 1. Our objectives were (i) to describe patient characteristics, treatment, and mortality of hospitalized older adults with COVID-19 between waves 1 and 3; and (ii) to determine if there was an improvement in mortality in waves 2 and 3 after adjusting for covariates. 

We included consecutive adults aged ≥65 years with COVID-19 infection confirmed with viral polymerase chain reaction (PCR), admitted to one of the included hospitals. We excluded (i) those who were readmitted to hospital after an index admission for COVID-19

and (ii) those with a false positive swab or recovered COVID-19 infection as defined by the site's infection control team.

Eligible patients were identified by the data analytics service at each site, using the same case detection protocol for public health reporting. A trained chart assessor abstracted data using standardized data abstraction form hosted on a REDCap database. 16 Each chart assessor was trained by a physician investigator at the hospital site (Barbara Liu, Jennifer Watt, Eric Wong, Katrina Piggott, and Richard Norman). The first five charts were extracted in duplicate with the physician investigator, and additional charts were reviewed as needed by the physician investigator when questions arose.

We extracted patient characteristics from the chart, including age at diagnosis, sex (as documented on chart), baseline functional status (as documented by physician consultation notes or occupational therapist note), place of residence, clinical frailty scale (CFS), 17 past medical history, and COVID-19 vaccination status (as documented on the admission consultation note). Functional status was documented using items of activities of daily living (ADLs) and instrumental activities of daily living (IADLs). 18 The CFS was a frailty measure that used clinical phenotypes. 17 Pharmacologic treatment for COVID-19 was recorded.

Delirium was assessed using a validated chart review tool. 19 Prevalent delirium was defined as identifying delirium keywords on the emergency medicine records or admission consultation. Incident delirium was defined as delirium keywords occurring in later notes during the hospital stay. Recorded outcomes included in-hospital mortality, intensive care unit (ICU) admission, and length of stay.

Missing data were reviewed by the site physician investigator.

Missing CFS was imputed as 6 (severe frailty) for LTC residents and 5 

Of the 1671 patients admitted to an acute care hospital during the study period (Table 1) 

Some medications were used empirically in wave 1. Significantly more patients received dexamethasone (71.5% vs. 3.0%, p < 0.001), remdesivir (16.8% vs. 0%, p < 0.001), and tocilizumab (2.4% vs. 0.3%, p = 0.046) in wave 2 than wave 1. The use of these medications increased in wave 3 ( Table 2 ).

There was no difference in the proportion of in-hospital deaths between waves 1 and 2 (26.2% in wave 2 vs. 27.4% in wave 1, p = 0.774), but unadjusted mortality was lower in wave 3 (18.3% vs.

27.4% in wave 1, p = 0.003). Delirium prevalence, delirium incidence, and ICU admissions were similar between waves 1 and 2 ( 

Using a multivariable model ( 

This multicenter retrospective cohort of consecutive older patients admitted to hospital with COVID-19 highlighted differences in the patient population, treatment, and mortality between waves 1-3 of the pandemic in Toronto, Ontario. Later waves involved younger patients with less frailty and fewer comorbidities, and they received significantly more evidence-based medications. However, after adjustment, the in-hospital mortality was similar between waves.

This finding is in agreement with published studies comparing the survival of ICU patients in waves 1 and 2 in Europe, where no improvement in survival was seen. 23, 24 Complicating waves 2 and 3 of the pandemic was the rise of SARS-CoV-2 variants. 25 In Ontario, Canada, the prevalence of variants increased from 15% of all cases in early February 2021 to 92% in June 2021. 26 Variant data was not captured in our study because researchers were not allowed to access the external health portal where variant sequencing results were hosted. The increased virulence of the variants 25 may explain the lack of improvement in mortality in the second wave, despite the prevalent use of disease-modifying drugs (e.g., 71%-76% on dexamethasone). Another explanation for the lack of mortality improvement in the latter waves may be related to the efficacy of the drugs in older adults. A systematic review of steroid trials in COVID-19 patients showed that the median age of trial participants ranged from 57 to 67, with few patients aged >80 years. 8 The lack of improvement in in-hospital mortality in subsequent COVID-19 waves suggests an opportunity to improve the care of older adults hospitalized with COVID-19 and future pandemics. First, clinical trials of therapeutic drugs should include those most impacted by the disease. In COVID-19, frail older adults were known to be most susceptible to death and complications early in the pandemic, 4 but trials of therapies mainly included younger adults. 8 When clinical trials of younger patients are applied to older adults, real-world efficacy may be decreased or unanticipated adverse events may occur. 27 Second, an aging population requires acute care facilities to be equipped to care for older adults, including an optimal physical design 28 and systems-level policy changes. 29 Third, physicians, nurses, and other allied health staff should undergo training for the care of older adults in school. Integrating geriatric training into an undergraduate curriculum allows for early exposure to best practices and person-centered care. 30 Strengthening geriatric care in hospitals increases staff resilience when encountering unexpected events, such as a future COVID-19 wave or another pandemic.

There are some limitations to our data. First, we retrospectively collected the data. Second, COVID-19 variants data were not recorded because not all hospitals had this recorded. Third, we did not collect other demographic characteristics such as gender, race, language, and socioeconomic status. Fourth, we did not include vaccination status in the final model because most patients tested positive for COVID-19 soon after their first dose (median: 14 days), so the vaccine was not expected to be sufficiently protective yet. 31 Fifth, we did not collect data on illness severity or supplemental oxygen use, which limited our ability to control for illness severity in the analysis.

There are several strengths to our study. We included consecutive older adults admitted to five academic acute care hospitals in Toronto. A geriatrician investigator supervised the chart review at each site using a consistent process. We abstracted delirium incidence using a validated chart review method. 19 Each patient was assessed until death or discharge from acute care. 

The authors declare no conflicts of interest.

Data available on request from the authors.

Research ethics approval was obtained through Clinical Trials Ontario (3186-OPIA-Apr/2020-38044).

The manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

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